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Participatory Action Research and Photovoice: Applicability, Relevance, and Process in Nursing Education Research

2020· article· en· W3040972805 on OpenAlexaff
Tracy Oosterbroek, Olive Yonge, Florence Myrick

Bibliographic record

VenueNursing Education Perspectives · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPhotovoiceParticipatory action researchRelevance (law)Action researchCitizen journalismQualitative researchMedical educationNursingData collectionProcess (computing)Nurse educationAction (physics)PsychologyNursing researchParticipant observationSociologyPedagogyMedicineComputer scienceSocial sciencePolitical science

Abstract

fetched live from OpenAlex

ABSTRACT: Participatory action research (PAR) is a philosophy and approach to qualitative research. The purpose of this article is to generate a clearer understanding of PAR and its relevance to the discipline and profession of nursing. The authors provide a description of the principles and process of implementing PAR methodology, using photovoice as an innovative, participant-directed data collection method in rural nursing preceptorship. Participants were undergraduate nursing students and faculty advisors assigned to rural communities during the final clinical preceptorship. Participants described opportunities and challenges experienced during the preceptorship and how these experiences influenced their learning and overall preceptorship experience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.215
metaresearch head score (Gemma)0.224
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.215
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2150.224
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0100.033
Scholarly communication0.0160.010
Open science0.0030.016
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.770
GPT teacher head0.752
Teacher spread0.018 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

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